{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00186616","sets":["1164:1384:9436:9437"]},"path":["9437"],"owner":"11","recid":"186616","title":["サンプリングに基づく分散悪性競合のオンライン検出"],"pubdate":{"attribute_name":"公開日","attribute_value":"2018-03-02"},"_buckets":{"deposit":"71d9cfbb-effe-4734-bba0-8f07247ff4c5"},"_deposit":{"id":"186616","pid":{"type":"depid","value":"186616","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"サンプリングに基づく分散悪性競合のオンライン検出","author_link":["419194","419193","419195"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"サンプリングに基づく分散悪性競合のオンライン検出"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"実行解析","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2018-03-02","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"東京工業大学"},{"subitem_text_value":"東京工業大学"},{"subitem_text_value":"東京工業大学"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Tokyo Institute of Technology","subitem_text_language":"en"},{"subitem_text_value":"Tokyo Institute of Technology","subitem_text_language":"en"},{"subitem_text_value":"Tokyo Institute of Technology","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/186616/files/IPSJ-SE18198026.pdf","label":"IPSJ-SE18198026.pdf"},"date":[{"dateType":"Available","dateValue":"2020-03-02"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-SE18198026.pdf","filesize":[{"value":"1.1 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"12"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"1a544dcc-82e0-45e9-9848-254eb4f5ef48","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2018 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"片平, 遥香"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"荒堀, 喜貴"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"権藤, 克彦"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10112981","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2188-8825","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"分散システム固有のバグとして分散並行バグ （DCbug） の存在が明らかになっている [2]．DCbug の検出手法として，マルチスレッド競合検出手法の適用はスレッド数が極度に多い分散システムではスケールしない．計算コストを減らすサンプリング手法を用いても，全体のごく一部である DCbug を検出するのは難しい．DCbug を検出する先駆者的手法として DCatch [1] が提案されているが，小規模な実行トレースをオフラインで検査するにとどまっている．本論文では，大規模分散システムに適用可能なオンライン DCbug 検出手法ポケットレーサを提案する．ポケットレーサは，データサンプリング，分散メタデータ簡約と呼ぶ二種類の最適化手法に基づく．データサンプリングは，システムの異常動作につながるフィールドアクセスがノード間通信に依存するかを識別することで DCbug の温床となるアクセスを重点的に調べるサンプリング法である．分散メタデータ簡約は分散システムに特化した VectorClock のバージョン管理方法ノードバージョン配列を導入し，VectorClock 配列全体へのコストの高い処理を削減することで，大規模分散システムにスケールする競合解析を実現する．実験では，代表的な四種類の分散データシステムに特徴的な通信パターンを捉えた合成ベンチマークに対してポケットレーサを適用するシミュレータを行った．実験結果としてポケットレーサは，既存のメインスレッドプログラムへの競合検出器に比べて同等以下の性能を維持し，DCbug の検出率は 4 倍以上となった．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"8","bibliographic_titles":[{"bibliographic_title":"研究報告ソフトウェア工学（SE）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2018-03-02","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"26","bibliographicVolumeNumber":"2018-SE-198"}]},"relation_version_is_last":true,"weko_creator_id":"11"},"updated":"2025-01-20T02:31:41.734876+00:00","created":"2025-01-19T00:53:33.430532+00:00","links":{},"id":186616}